Exploratory Data Analysis & Data Wrangling

Getting the Data

fredr_set_key('07d43cd27b8d103658e01cf077124b24')

fredr(
  series_id = "M2SL")
) -> m2_sa #M2 monetarni agregat

fredr(
  series_id = 'MSPUS'
) -> median_house_price_nsa 

fredr(
  series_id = 'USSTHPI'
) -> house_price_index_nsa

fredr(
  series_id = 'WPU159402'
) -> jwlr_ppi_nsa #kompozitni index cen au, ag, pt

fredr(
  series_id = 'CSUSHPISA'
) -> sp500_sa 

fredr(
  series_id = 'LES1252881600Q'
) -> wag_median_sa #median wage

fredr(
  series_id = 'GNPC96'
) -> gnp_sa

fredr(
  series_id = 'MORTGAGE30US'
) -> mtg_30_nsa

fredr(
  series_id = 'MSACSR'
) -> hs_sale-sold_sa #houses for sale/houses sold

fredr(
  series_id = 'CPIAUCSL'
) -> cpi_sa

df_indices %>% 
  ggplot(data = .,
         aes(x = date)) + 
  geom_point(aes(y = MSPUS, color = 'median house price')) +
  geom_point(aes(y = CPIAUCSL, color = 'cpi')) +
  geom_point(aes(y = GNPC96, color = 'GNP')) +
  geom_point(aes(y = USSTHPI, color = 'HousePrice index')) +
  geom_point(aes(y = WPU159402, color = 'MetalsPrice index')) +
  geom_point(aes(y = M2SL, color = 'M2 Aggr.')) + 
  geom_point(aes(y = MORTGAGE30US, color = 'Mortgaege30Y rate')) +
  geom_point(aes(y = CSUSHPISA, color = 'S&P500')) + 
  geom_point(aes(y = LES1252881600Q, color = 'MedWage')) +
  scale_y_log10(name = 'log Value') +
  ggtitle('MacroVars Composite Plot') +
  scale_x_date(breaks = scales::breaks_pretty(100)) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))-> plot_composite
  
plotly::ggplotly(plot_composite)